{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bài viết tham khảo tại [nguồn](https://www.pyimagesearch.com/2019/10/28/3-ways-to-create-a-keras-model-with-tensorflow-2-0-sequential-functional-and-model-subclassing)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ví dụ thêm về việc sử dụng Subclassing để viết custom layer hoặc custom class"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://www.tensorflow.org/guide/keras/custom_layers_and_models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1. Thêm các thư viện cần thiết"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "from tensorflow.keras.models import Model\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import BatchNormalization\n",
    "from tensorflow.keras.layers import AveragePooling2D\n",
    "from tensorflow.keras.layers import MaxPooling2D\n",
    "from tensorflow.keras.layers import Conv2D\n",
    "from tensorflow.keras.layers import Activation\n",
    "from tensorflow.keras.layers import Dropout\n",
    "from tensorflow.keras.layers import Flatten\n",
    "from tensorflow.keras.layers import Input\n",
    "from tensorflow.keras.layers import Dense\n",
    "from tensorflow.keras.layers import concatenate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2. Thiết kế model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MiniVGGModel(Model):\n",
    "    def __init__(self, classes):\n",
    "\n",
    "        super(MiniVGGModel, self).__init__()\n",
    "    \n",
    "        # Block 1\n",
    "        self.conv1A = Conv2D(64, (3, 3), padding=\"same\")\n",
    "        self.act1A = Activation(\"relu\")\n",
    "        self.bn1A = BatchNormalization()\n",
    "        \n",
    "        self.conv1B = Conv2D(64, (3, 3), padding=\"same\")\n",
    "        self.act1B = Activation(\"relu\")\n",
    "        self.bn1B = BatchNormalization()\n",
    "        \n",
    "        self.pool1 = MaxPooling2D(pool_size=(2,2))\n",
    "        \n",
    "        \n",
    "        # Block 2. Padding Same nghĩa là duy trì kích thước đầu ra tương tự đầu vào, phần bị lược bỏ bằng Kernel sẽ \n",
    "        # được thay thế bằng 0.\n",
    "        \n",
    "        self.conv2A = Conv2D(32, (3, 3), padding=\"same\")\n",
    "        self.act2A = Activation(\"relu\")\n",
    "        self.bn2A = BatchNormalization()\n",
    "        \n",
    "        self.conv2B = Conv2D(32, (3, 3), padding=\"same\")\n",
    "        self.act2B = Activation(\"relu\")\n",
    "        self.bn2B = BatchNormalization()\n",
    "        \n",
    "        self.pool2 = MaxPooling2D(pool_size=(2,2))\n",
    "        \n",
    "        # 2 Block này gần giống nhau dùng Conv2D để trích xuất đặc trưng của anh và loại bổ data không cần thiết.\n",
    "        # Đầu ra của hàm Activation (Phi tuyến) sẽ được chuẩn hoá lại BatchNorm nhằm đảm bảo qua mỗi block, phân\n",
    "        # bố của anh không bị thay đổi quá nhiều\n",
    "        \n",
    "        \n",
    "        self.flatten = Flatten()\n",
    "        self.dense3 = Dense(512)\n",
    "        self.act3 = Activation(\"relu\")\n",
    "        self.bn3 = BatchNormalization()\n",
    "        self.do3 = Dropout(0.5)\n",
    "        \n",
    "        # Sau khi qua mạng trích xuất đặc trưng data được duỗi thành cỡ 512*1 và đưa vào một neural network không \n",
    "        # kết nối đầy đủ với tỉ lệ Dropout là 0.5 (Kỹ thuật Dropout là kỹ thuật tắt một số lượng nút trong mạng bất kỳ)\n",
    "        # dựa trên một tỉ lệ cho trước\n",
    "        \n",
    "        self.dense4 = Dense(classes)\n",
    "        self.softmax = Activation(\"softmax\")\n",
    "        \n",
    "        # Mạng Neural Network này có đầu ra là một lớp Softmax với 10 nhãn cho trước.\n",
    "        \n",
    "    \n",
    "    def call(self, inputs):\n",
    "        \n",
    "        # Block 1. Lần lượt đưa dữ liệu qua các lớp.\n",
    "        \n",
    "        x = self.conv1A(inputs)\n",
    "        x = self.act1A(x)\n",
    "        x = self.bn1A(x)\n",
    "    \n",
    "        x = self.conv1B(x)\n",
    "        x = self.act1B(x)\n",
    "        x = self.bn1B(x)\n",
    "        x = self.pool1(x)\n",
    "        \n",
    "        \n",
    "        # Block 2\n",
    "        \n",
    "        x = self.conv2A(x)\n",
    "        x = self.act2A(x)\n",
    "        x = self.bn2A(x)\n",
    "        \n",
    "        x = self.conv2B(x)\n",
    "        x = self.act2B(x)\n",
    "        x = self.bn2B(x)\n",
    "        \n",
    "        x = self.pool2(x)\n",
    "        \n",
    "        # Block 3\n",
    "        \n",
    "        x = self.flatten(x)\n",
    "        x = self.dense3(x)\n",
    "        x = self.act3(x)\n",
    "        x = self.bn3(x)\n",
    "        x = self.do3(x)\n",
    "        \n",
    "        \n",
    "        # Block 4\n",
    "        \n",
    "        x = self.dense4(x)\n",
    "        x = self.softmax(x)\n",
    "        \n",
    "        return x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.Tải dữ liệu và chuẩn hoá"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"./img/cifa.png\" width=600/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow.keras.datasets import cifar10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "((trainX, trainY), (testX, testY)) = cifar10.load_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hiển thị mẫu một số ảnh trong bộ dữ liệu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 25 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "class_names = ['airplane', 'automobile', 'bird', 'cat', 'deer',\n",
    "               'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "for i in range(25):\n",
    "    plt.subplot(5,5,i+1)\n",
    "    plt.xticks([])\n",
    "    plt.yticks([])\n",
    "    plt.grid(False)\n",
    "    plt.imshow(trainX[i], cmap=plt.cm.binary)\n",
    "    # The CIFAR labels happen to be arrays, \n",
    "    # which is why you need the extra index\n",
    "    plt.xlabel(class_names[trainY[i][0]])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Đưa dữ liệu về trong khoảng (0,1). Tại sao phải làm như thế này thì tôi đã giải thích tại bài trước. [Xem ở đây](./setup-and-first-code.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainX = trainX.astype(\"float32\") / 255.0\n",
    "testX = testX.astype(\"float32\") / 255.0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nhãn được đánh từ 0 đến 9 tương đương với danh sách dưới đây"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "labelNames = [\"airplane\", \"automobile\", \"bird\", \"cat\", \"deer\", \"dog\", \"frog\", \"horse\", \"ship\", \"truck\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Chuyển về dạng one hot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One hot chỉ là cách chuyển nhãn về sao cho đảm bảo tính tương đồng của các nhãn với nhau. Hình ảnh dưới đây minh hoạ ma trận onehot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"./img/onehot.jpeg\" width=600/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelBinarizer\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "from tensorflow.keras.optimizers import SGD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "lb = LabelBinarizer()\n",
    "trainY = lb.fit_transform(trainY)\n",
    "testY = lb.transform(testY)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 0, 1, 0],\n",
       "       [0, 0, 0, ..., 0, 1, 0],\n",
       "       ...,\n",
       "       [0, 0, 0, ..., 0, 0, 0],\n",
       "       [0, 1, 0, ..., 0, 0, 0],\n",
       "       [0, 0, 0, ..., 1, 0, 0]])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testY"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4. Tăng cường data khi train"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ta có thể xoay, zoom to, thay đổi kích cỡ để có nhiều đặc trưng hơn mà vẫn giữ nguyên nhãn"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Xem kỹ hơn về tăng cường data [tại đây:](https://github.com/bangoc123/learn-machine-learning-in-two-months/blob/master/data-processing/ImageAugmentation.ipynb?fbclid=IwAR2WIgr3FqjGRhWaFENLiFEl4MPO4HKGfGUmRIIsM54EF_bF8_3QhsDN7rg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "aug = ImageDataGenerator(rotation_range=18, zoom_range=0.15, width_shift_range=0.2, height_shift_range=0.2, shear_range=0.15, horizontal_flip=True, fill_mode=\"nearest\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = MiniVGGModel(len(labelNames))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 5. Đặt các hyperparameter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "learning_rate = 1e-2\n",
    "batch_size = 1024\n",
    "num_epochs = 1 # Accuracy: 74% within 30 epochs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sử dụng thuật toán tối ưu Stochastic gradient descent thay vì feed toàn bộ data trong mỗi epoch mà chia thành từng batch nhỏ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "opt = SGD(lr=learning_rate, momentum=0.9, decay=learning_rate / num_epochs)\n",
    "model.compile(loss=\"categorical_crossentropy\", optimizer=opt, metrics=[\"accuracy\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tiến hành training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start Training...\n",
      "48/48 [==============================] - 378s 8s/step - loss: 1.9842 - accuracy: 0.3181 - val_loss: 1.9834 - val_accuracy: 0.2593\n"
     ]
    }
   ],
   "source": [
    "print(\"Start Training...\")\n",
    "H = model.fit_generator(aug.flow(trainX, trainY, batch_size=batch_size), validation_data=(testX, testY), \n",
    "                        steps_per_epoch=trainX.shape[0] // batch_size, epochs=num_epochs, verbose=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save model lại."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow_core/python/ops/resource_variable_ops.py:1781: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "If using Keras pass *_constraint arguments to layers.\n",
      "INFO:tensorflow:Assets written to: final/assets\n"
     ]
    }
   ],
   "source": [
    "model.save(\"final\", save_format='tf')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 6. Kết quả và Inference"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tôi đang train trên Colab gần xong rồi, khi nào có kết quả sẽ viết tiếp phần Inference. Độ chính xác đang là 77%"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"./img/training.png\" width=600/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 7. Inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "((_, _), (inferenceX, inferenceY)) = cifar10.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x138774c50>"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPsAAAD5CAYAAADhukOtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAe7ElEQVR4nO2daYyc13Wm31NfLb1vbLLZXEVJlBVZiSmF1tiJRpGdcaAoCWQDgccewFAAIwqCCIiBzA/BA4w9wPxwBmMb/jHwgB5rrBgeyxrbgoREyNiWgwiGHUnURi3UQnGRSDbZJJu9d+1nflTJQ2nue7vJZlfTvu8DEKy+p+/3nbr1nfqq71vnHHN3CCF+/cmttwNCiM6gYBciERTsQiSCgl2IRFCwC5EICnYhEiG/mslmdgeArwHIAPwPd/9S7Pf7u/O+YaAYPlb8PBftW0xSdHBb9FxkWvR4/Ghxo8feh2P+h20WOxmZAwAxZfbSZFvuR+xo7hd/DbSOydaD04w+6UvzI/bsmKUZcYP5OLNQx1KlEXTykoPdzDIA/w3AxwAcB/C0mT3q7q+wORsGivjCv7s+fDxv0nMVC2E3LccDolqtUFu9UePnKobfjACg0Qz76JFXxXINastl1ASv9fJjgh+zUCwHx7PIS2057n+jWae2Wp2/Zs0mCQrjftTD1ygAoMKOh+UCN+xj7E29WuXXR6MRWcfINZyLvGZVcl0t8KXHYjV8vG//5ETEh0vnFgCH3P2wu1cBPAjgrlUcTwixhqwm2LcCePuCn4+3x4QQVyBrvkFnZveY2X4z2z+/FPlcIoRYU1YT7CcAbL/g523tsXfh7vvcfa+77+3rXtV+oBBiFawm2J8GsNvMdplZEcCnADx6edwSQlxuLvlW6+51M7sXwP9BS3q7391fjs6BoUreX9yX+ESyW1kC37HOgW915/ORHfJLULyswCdVqlVqqzcjPkaktyyyi58n06zJd5hR58pFbBe5GfG/al3B8UZW4nNix2vw9bAm99GImtAVec3yxm25fES5qEXW2PifsE7W2CM6Q5aFfYwpE6v6XO3ujwF4bDXHEEJ0Bn2DTohEULALkQgKdiESQcEuRCIo2IVIhA5/y8XhLLHCufzjjfAca3CpplnjklfWHZFxwJMZmOTVjEg/xUKB2urObc1a5LlFzlevh20WyeTKRWQ+y3hikGdheQ0Alhphie3UOS5PLVS5j/PzfF7mfD36u8LrWDT+Og/0dFNbd4lLaM0cv+ZyURkt7CO/OoAaS76KaG+6swuRCAp2IRJBwS5EIijYhUgEBbsQidDR3XhzR75Bdt2zyG4xSeIoZZH8+HxsWzKS6EASDADQRJh6rFhYjvtRKPJd381XXUdts9Nnqe3sucXwufJ8Vz2HSHJKnV8iS879P3gs7KOXRuicWsYTm6p9fOd/fmaK2k5MTgfH+0r8eTVOhecAwI4xvo4b+vk6duVj5azC13Excgk3iAIRK7elO7sQiaBgFyIRFOxCJIKCXYhEULALkQgKdiESYR3KvYalAcsP8RlETqjHOnDkuCxXrfOEhWKkRlqjQWqFRRJTEJFCipE6aP/q33yM2p75+S+o7eT0ueD4QkRCqze45HXs+BlqO3KCdx8pDY0Hx7eN7aJzvNRPbdU8f10KfRuprV6eD46fmzxJ5/QMcXnw+PxpaiuTWokAMNbP01p6CuFEmEYtLKMCAGviE+nkpTu7EKmgYBciERTsQiSCgl2IRFCwC5EICnYhEmFV0puZHQUwB6ABoO7ue2O/37QcKrmwvDKz2EPnNUh7ouE+Lq8NZFwOy0fqsTUjshyTNWhdPcSz6BYXz1PbT//+EWo7Pc3r9Z2eD5/v2Al+rmMTb1Nb1tVHbY1sgNp6B0aD44Uefrx8F8+iK0VaMnXluHR4thpuKza+bQedU15aoLYjR7j0NjVTprbM+PO+amPYVmhwKc9YXcaI1Hs5dPaPuDvPuRRCXBHoY7wQibDaYHcAPzKzZ8zsnsvhkBBibVjtx/hb3f2EmW0C8GMze9Xdn7jwF9pvAvcAwHA/r/IhhFhbVnVnd/cT7f8nATwM4JbA7+xz973uvrevex2+ii+EALCKYDezXjPrf+cxgD8A8NLlckwIcXlZza12DMDD7a3+PID/5e7/GJtQbxrOLIUzfKZqPOvtiZ//c3D8N3ZzyeUj7w9LPwAwHClu2SSZbQCQI216cjme0dRw3rYooibhyLEj1Da1xDPAvGc4OJ71ceknNzxHbd1Dg9RWLXOpqUraKw0M89dsoI/bJk+dorbZ87zgZH8xfIl3dXOZ763zXFwq9G+itjOn3qK2vtN8jTcPhH3ptkimIinCioisfMnB7u6HAXzgUucLITqLpDchEkHBLkQiKNiFSAQFuxCJoGAXIhE62+stKyE/GC44uHiOv+/UiuGCglOLYSkMABarvDfYQJFntjVJ3622MTicZTxjr1zlEs8ZnryGs3NcAowVRBzeGM7mWmjO0jmj4D5mkUy0aoGvY3khLDWV57kfO8c2UNsikdAAYJJktgGAFcIy5cwUL+aISAHRpQWeEZcV+XUwOcuzDidIttzOUX5951hCXKzFITcJIX6dULALkQgKdiESQcEuRCIo2IVIhI7uxnd19+J9v/X/ZcECAI7/y2t0Xt9geDf+lg+HjwUAPdkxaquSnWIAyOV5UosVwjvTDedJPP2btlPb8wcOUVvfEN+Z3rrz/dTmufDucyGyc96shFtGAUC1GmmxFVmrjCRxvPzCATpnoBRpkdTLk2R6I3XtTp4K14yrE2UFADKygw8Aw/1cnZhp8KSn81PcduTUTHB8y9hmOifPFKVIdpXu7EIkgoJdiERQsAuRCAp2IRJBwS5EIijYhUiEjkpvuSyPnsGwpLTz6uvovCWiWuzYdS2dM1rj0sr0ES7L1SKJMI16ONHhlts+TufsuJp3xNr1m0ep7ZnnXqC24T4uyZycDNdPyzsv410qcMkLfBkxH0kKmSF14YZ7+bkip0IjIpWNbgxLswBQqYVfz7Pnw3IXAFikZVd/pE5ePuPhVC3zxJvDbx8Pjm8c4jLf7m3hNmoeuX/rzi5EIijYhUgEBbsQiaBgFyIRFOxCJIKCXYhEWFZ6M7P7AfwxgEl3v7E9NgLgewCuAnAUwCfdnRfZeudYuRyyUjhD6eTpg3Tent/+YHC8d5DX/MrmTlBbox5pkROpdXb47XC23K3D4bp6AICebdTU38vlmK48z+TqjtQ66yqSjK1IXbWtW8ap7ZU336S2YpHX+ZudC6/VVdt20znXXX8DtU1N8curb4BnHZ48NRkctxyv7zY0zGv8zURqyWURya67h/u4NBe+Dg6R6w0Auovhc9XqkSxFavl/fAvAHe8Zuw/A4+6+G8Dj7Z+FEFcwywZ7u9/6e78hcReAB9qPHwDAv1UihLgiuNS/2cfcfaL9+BRaHV2FEFcwq96gc3dH5JuOZnaPme03s/0zM7xmuBBibbnUYD9tZuMA0P4/vAsCwN33ufted987ODhwiacTQqyWSw32RwHc3X58N4BHLo87Qoi1YiXS23cB3A5g1MyOA/gCgC8BeMjMPgvgGIBPruRkZhkKXeG7e7nMCyJWKuG0t0JEgurp5Z8ieiMtjUoZz3rry4f7NX1r3zfpnD/5t/dSW2HhFLUVS5HspRz3cdfVW4Pjk1Mn6ZzyPM9e27xplNqmZrl0WKmGX8+rr+WZitdcyzMfZ557ltoW5uapbXYh7GO9wSWqpaVwOyYAGBoapLaGc6lsYIhn+9Wr4dczy/H+YMcnwh+mqyTLD1hBsLv7p4np95ebK4S4ctA36IRIBAW7EImgYBciERTsQiSCgl2IROhowUmYwbKwBLEYkX/Ki0vB8UKkJ9fcOZ7lhYxLbwXwQoTjQ+FMqTcO8p5tJ49zGxa5HHbs+FFqu2kz73G3dWe4GOWWSf6N5oVDvADnSCnSx26Iy3KHDx8Njo9vCUuDADA9y79hWYtIZafP8F51TbfguEWKQy5GpDfL8esqfKYWvZFClWiGs+yKFr7uAaB6LizbeqRsp+7sQiSCgl2IRFCwC5EICnYhEkHBLkQiKNiFSITOSm8OgPTsypxLK+Oj4f5wPV1cevvpAV4ocThSlG/3CM9O6iqFZZdinks1ZyaPUluzwosX7riGF7HMIs+7Z2A4OD46xgtfnpviWWMzkcy2RkTd3Ej6r+UjcmmZZH8B8WyupTLPDqsTJ9k4AJQrPAOzXuf3xw2jm6jNjF9XRQtfPyWL9B30cMZnIVL0Und2IRJBwS5EIijYhUgEBbsQiaBgFyIROrobbwYU8uFkksE+npwy1B+2WZPvVs46Tzw4e56nLIz28yXpLYZ3VBu5cI08ADh68ii1jQ3zemY7r+WtkMr8dHjqmXAbrRMTfOe/vy+8gw8AhQJv8fTyobe4I+Q+0ozcXyqR3fj5BZ4UMjTC2zXVSSLMxGlaEBm9/fx1yWc80aSnh9dELLK2XABQCyfyNBam6ZSxTf3B8XyBt7XSnV2IRFCwC5EICnYhEkHBLkQiKNiFSAQFuxCJsJL2T/cD+GMAk+5+Y3vsiwD+HMCZ9q993t0fW8kJMwtLIZs3hWuntZwkMk4kAWJ8G08k2R+Rw6aNS3aehevkDY7ypIrBAZ4AUegKyycAcFVEeusbDCcGAcD/vP/bwfHFyFrNLk1R2+ISrw1YiFw9m4fDz7s8xevdLZBEIwAYHOCvy6uvvUFtp0+fCY7PRlpGDQ3xJzbQ20dtmXNNtFDl65iRWoQbe/nxBrvCcZSP3L5Xcmf/FoA7AuNfdfc97X8rCnQhxPqxbLC7+xMA+Fu/EOJXgtX8zX6vmR0ws/vNjH8FSwhxRXCpwf51ANcA2ANgAsCX2S+a2T1mtt/M9k9P86//CSHWlksKdnc/7e4Nd28C+AYA2rXA3fe5+1533zs0xBsOCCHWlksKdjMbv+DHTwB46fK4I4RYK1YivX0XwO0ARs3sOIAvALjdzPagVVXuKIC/WMnJcrkczf4ZGObSW70RdrOU55lE1+3aQW37n+GS12zhWmpr2lxwfGwrl9deOfgv1PY7v/dn1PaLn/N5CwuRNknVs8HxyVNv0zmx9/z5GrflwaWh4Vw4y25rN/d95gyX0OoZ3xYa28RtjUY4k24p0uKpvMTr7i1EaujVm1zOq5VPUNumQjijb0sfz6Kr1MNzYnfvZYPd3T8dGP7mcvOEEFcW+gadEImgYBciERTsQiSCgl2IRFCwC5EIHS04mcvl0NsXzl4aHh2l8+oWdrOcK9I5XX0D1DY0xAsKvvX2KWq79YPvD/sxz9tJ9fSHs64AYOLEcWo79Prr1FZv8PZEOVJvcGF2hs7p3zBObTMzXIYa7OPFKN933Y3B8adfeJXOefbVo9R26+1/SG2FIpeoDh86FByfmePPK1YUs7zE5bWdY1zS7e7lBVVHRsLzPM8LcNar4cKXTrJKAd3ZhUgGBbsQiaBgFyIRFOxCJIKCXYhEULALkQgdld7cm2jWw5LH4Agv5LewFC5EuNjgfbeyjL+P7di+jdpef5lnXs0shiW2vl6eYbf9GmrCsdd58cUTJyeo7cMf/iC1LS6GpaH+LVvpnJEtvDjnW1NcKluqcMmx2BvuvzawcTudc1M/f13OnAn3QwOAo8deoLaFpbBMOT3DJbSNGzdS26Dz12VnH5dENw3wHmwFC2cCVmu8v10vkdhy4DGhO7sQiaBgFyIRFOxCJIKCXYhEULALkQgd3Y1v1muYOxfezeyO1PaqlMO7nNbk7pvxXcnREd4+6fXcYWqbnAq38DmX8V3pwT5eW+/6G3lCzuFjvGZcjXdJwvRsWO3YvXs3nbN7F5cMjk3wBJqXX36R2s6dDSenFEtcdRnu44kkx1/mqsCpc7yunZFkqSzSeivWOmwnzzPBjn6eGNSV40ktlXL4+mk2eW3DWp0cj1/2urMLkQoKdiESQcEuRCIo2IVIBAW7EImgYBciEVbS/mk7gL8DMIbWxv4+d/+amY0A+B6Aq9BqAfVJdw/3/GlTqVRw+FBY2tqx+zfovK5cWHprVnmiQL4rIoNEbP39XBrqGwjXtbv++vfROT/50WPUtjjD6931jGyitkPHJ6lt+7ZwUs6u991M55SK/DK4egdP8pme4i/3KwfDCUVN57rhiWmeSDJLkqEAoNzgsu3sdFiK3LSZJ928dY7XpxvZzuXScyXuB5r8uU3Xw8/N8/w6rZDjVcETblZyZ68D+Bt3vwHAhwD8lZndAOA+AI+7+24Aj7d/FkJcoSwb7O4+4e7Pth/PATgIYCuAuwA80P61BwB8fK2cFEKsnov6m93MrgJwE4AnAYy5/zK59xRaH/OFEFcoKw52M+sD8AMAn3P3d30/0d0d5It6ZnaPme03s/1zc7xggBBibVlRsJtZAa1A/467/7A9fNrMxtv2cQDBXSN33+fue919b2zzSwixtiwb7GZmaPVjP+juX7nA9CiAu9uP7wbwyOV3TwhxuVhJ1tvvAvgMgBfN7Pn22OcBfAnAQ2b2WQDHAHxyuQMtVup4/lBYNtpx4y10XhPhbDNjmT8A0OTpP7Nzc9Q2PX2W2jaM7AmO33nHR+icPR+4ntoe+uHD1GbGJZTBwWFq27olLCn1DQzROVk9vL4AMLKZXyLju2rUNtMdlo2ee4HXi5uY5yllXuDtvAY38yzG0WvCUlkWkbUazv14zcPtywDg0CkuDxYzfsylcjk4vhi5vOvN8PUx1+DZgcsGu7v/DADz9PeXmy+EuDLQN+iESAQFuxCJoGAXIhEU7EIkgoJdiEToaMHJcsPw+kx30Ha2wQsAeiEsTeSqvBiiE2kCAHI5btsyzrPN/vXvhDPHugpcctm1k7dd+qM//RS1ff/hf6C2s6f4856YCRcvLJcP0TlFcI1naonbDh3jWXuohmU5H+UZgsObwkUqAaAZqaTY+s4XmdcVPmbTwoUoAaAWaSs20+Dn6irwY3blufS2YOEsu1qBn8ub4fVtRCRb3dmFSAQFuxCJoGAXIhEU7EIkgoJdiERQsAuRCB2V3ioNw+vT4feXR37G+4bt2TkaHN9c5BlIPYVIttZm3n9tfJRnV11zNSlS6LyY4MSZc9R2/4NcXnv2+VeojfW+AwCaCOj8fd0b/HiNEl+PRo5LQ3mEJdZ6RBqq58JzAKArdqVGstTK1fDz9hyfk49kxGVN3tfPy1ymrIPPKzTDPmbGX7NqLex/pMWh7uxCpIKCXYhEULALkQgKdiESQcEuRCJ0dDe+AcN8Lpws8Pizr9N5b7wZbhl1x2/fQOdcs4W36TlyONyaCABu++CN1NZFEhPmqnyH+aF/fJrannvlJLUt1iOthCK7xblC+P27GanJlzO+ixzbtW40eQJQheww1xp8jhmvaVdBJCnE+XPL58lOd8bvcz09PKGlCO5/g2+4o2E81BpkYr3GX5dif7imoOX4eXRnFyIRFOxCJIKCXYhEULALkQgKdiESQcEuRCIsK72Z2XYAf4dWS2YHsM/dv2ZmXwTw5wDOtH/18+7+WPRk+Tw2jG4M2qbOc/lk4vx0cPznL/BWN43azognXFrZuJkkuwCwLCyHPbX/JTrnH376C2qrNHnNNeS59JbLXfx7dKPCk108Iss1I/JaTPJiLZQKeX7JWcYlTGT8NctH5mVZ+HyxJqNZZH1zzuXBRiTZqBmRDplmt3kzl4/7B8K2N0uRdeIe/JI6gL9x92fNrB/AM2b247btq+7+X1dwDCHEOrOSXm8TACbaj+fM7CAAXjJVCHFFclGfB83sKgA3AXiyPXSvmR0ws/vNjLcWFUKsOysOdjPrA/ADAJ9z91kAXwdwDYA9aN35v0zm3WNm+81sf32Jt0oWQqwtKwp2a1Xh/wGA77j7DwHA3U+7e8PdmwC+ASDYYN3d97n7Xnffm+/mjSCEEGvLssFuZgbgmwAOuvtXLhgfv+DXPgGAb0kLIdadlezG/y6AzwB40cyeb499HsCnzWwPWnLcUQB/sdyBzIzKJIUCl5rq5bCccPT0LJ1TWThIbbfdfB21dQ+NU9tMOSyR/POT++mcsvPMpVqdyzilEs9sa0bqoC0uhlsJxcgiGVnGk94Q6ciEEpG8YllZiNisxGXK7m5euy5PpL5aJKNsbmGB2hoRmbJS56/L4HC4jiIAjI2HbX2RwntLc+E/iT1ybaxkN/5nAEIveVRTF0JcWegbdEIkgoJdiERQsAuRCAp2IRJBwS5EInS04CTc0ayTLKpYxlAWlqGq4NlOk/MVanv2NV7o8c5FLq3MeVjuOHGefzOw1Mezq+qL3P9yhfvf0xORmkjbq9jxLMf9yEXaNcUy2JzIaB65vxQicuN8jWffVetcKmOyXCxjLyahLURab/UNcXltaCNvOVath4/52qs8q7NAshFrVe6f7uxCJIKCXYhEULALkQgKdiESQcEuRCIo2IVIhA5LbwBY1pBzuSPLwsX6ms5loUaOF/g7Osmlsvsf4vk9H719b3D8yMkzwXEAWGzEihBGZKguXjgwK3JbD+lhVuzmstbSHJeuYtlhHpGoCiRjK8vz1yx2rixSVDLWx25pcf6i58TONTQ8Qm0bxnjG5NlzU9Q2ffZUePwt3pPw2l27woaIpKg7uxCJoGAXIhEU7EIkgoJdiERQsAuRCAp2IRKho9Jbls8wMjQUtJXLXA5bWApn8hQznv1Vj8hCuUhxyyeeOkBtR06Gs+VmFnjhyKn5JWojyU4AgN7eSLZcpKhgqRR+bvmIXNfVzTPKskhGXL7Aj9kg95F6RPKyiM2d+9io8fWv1sKL3N3FpcjRDRuobXiUy2vVSOZmpRgpHkn6szXzXD5eKIevq2ZEwtadXYhEULALkQgKdiESQcEuRCIo2IVIhGV3482sC8ATAErt3/++u3/BzHYBeBDABgDPAPiMu0f2lwFvOipkF7EUedupNMK7rYWM7wbX+SYyPMdPluvmu+DHSMJLLpLcUa/xHeaYYlAul6ltIdKeKEeeG9ulB4DeIt/17Y4k0ORy3P9iV/h83T18fatVnghzdoonkjTB5+UL4fUYHuilc8ZGwooRAGzezBNhphd4nb+56fPUNj8zHRwfGuHnOnvmbHC8HkkmWsmdvQLgo+7+AbTaM99hZh8C8LcAvuru1wI4D+CzKziWEGKdWDbYvcU7eYKF9j8H8FEA32+PPwDg42vioRDisrDS/uxZu4PrJIAfA3gTwLT7L1uUHgewdW1cFEJcDlYU7O7ecPc9ALYBuAXA9Ss9gZndY2b7zWx/bZG3WBZCrC0XtRvv7tMA/gnAhwEMmf2ysfc2ACfInH3uvtfd9xZ6BlblrBDi0lk22M1so5kNtR93A/gYgINoBf2ftn/tbgCPrJWTQojVs5JEmHEAD5hZhtabw0Pu/vdm9gqAB83sPwN4DsA3lztQs9lEZSksKZUyo/N6iJfNGk8yiXQtQhNcMoolEjRJu6l6NZLA0eDPK9aCKGZrRhJhmPR2/jyXfqYi6zjQxyWqwUg9tgFSC68LXMprNLl0lbdIsk6Jv9iVcviYpTx/XWLnqi/ORGzc//npc9TWJMk6XSUuiZZZnTyLPC9qaePuBwDcFBg/jNbf70KIXwH0DTohEkHBLkQiKNiFSAQFuxCJoGAXIhEsJvFc9pOZnQFwrP3jKIBw6k5nkR/vRn68m181P3a6+8aQoaPB/q4Tm+1393DzNPkhP+THZfdDH+OFSAQFuxCJsJ7Bvm8dz30h8uPdyI9382vjx7r9zS6E6Cz6GC9EIqxLsJvZHWb2mpkdMrP71sOHth9HzexFM3vezPZ38Lz3m9mkmb10wdiImf3YzN5o/z+8Tn580cxOtNfkeTO7swN+bDezfzKzV8zsZTP76/Z4R9ck4kdH18TMuszsKTN7oe3Hf2qP7zKzJ9tx8z0z4xVXQ7h7R/8ByNAqa3U1gCKAFwDc0Gk/2r4cBTC6Due9DcDNAF66YOy/ALiv/fg+AH+7Tn58EcC/7/B6jAO4uf24H8DrAG7o9JpE/OjomgAwAH3txwUATwL4EICHAHyqPf7fAfzlxRx3Pe7stwA45O6HvVV6+kEAd62DH+uGuz8B4L21ke9Cq3An0KECnsSPjuPuE+7+bPvxHFrFUbaiw2sS8aOjeIvLXuR1PYJ9K4C3L/h5PYtVOoAfmdkzZnbPOvnwDmPuPtF+fArA2Dr6cq+ZHWh/zF/zPycuxMyuQqt+wpNYxzV5jx9Ah9dkLYq8pr5Bd6u73wzgDwH8lZndtt4OAa13drTeiNaDrwO4Bq0eARMAvtypE5tZH4AfAPicu7+rOmkn1yTgR8fXxFdR5JWxHsF+AsD2C36mxSrXGnc/0f5/EsDDWN/KO6fNbBwA2v9ProcT7n66faE1AXwDHVoTMyugFWDfcfcftoc7viYhP9ZrTdrnvugir4z1CPanAexu7ywWAXwKwKOddsLMes2s/53HAP4AwEvxWWvKo2gV7gTWsYDnO8HV5hPowJqYmaFVw/Cgu3/lAlNH14T50ek1WbMir53aYXzPbuOdaO10vgngP6yTD1ejpQS8AODlTvoB4LtofRysofW312fR6pn3OIA3APwEwMg6+fFtAC8COIBWsI13wI9b0fqIfgDA8+1/d3Z6TSJ+dHRNAPwWWkVcD6D1xvIfL7hmnwJwCMD/BlC6mOPqG3RCJELqG3RCJIOCXYhEULALkQgKdiESQcEuRCIo2IVIBAW7EImgYBciEf4vt7E0CnHQV6IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(inferenceX[0], cmap=plt.cm.binary)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = model.predict(np.array(testX[0:1]/255.0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.argmax(result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 8. Load pretrain Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "VGG for CIFAR 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://github.com/geifmany/cifar-vgg/blob/master/cifar100vgg.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
